## No trace type specified:
## Based on info supplied, a 'scatter' trace seems appropriate.
## Read more about this trace type -> https://plot.ly/r/reference/#scatter
## No trace type specified:
## Based on info supplied, a 'bar' trace seems appropriate.
## Read more about this trace type -> https://plot.ly/r/reference/#bar
data_0713 <- as.data.frame(date_covid19.mask("2020-07-13"))
mask.data_0713 <- lm(COVID_CASE_RATE ~ obs_mask + PERCENT_POSITIVE + POP_DENOMINATOR, data_0713)
nomask.data_0713 <- lm(COVID_CASE_RATE ~ PERCENT_POSITIVE + POP_DENOMINATOR, data_0713)
summary(mask.data_0713)
##
## Call:
## lm(formula = COVID_CASE_RATE ~ obs_mask + PERCENT_POSITIVE +
## POP_DENOMINATOR, data = data_0713)
##
## Residuals:
## Min 1Q Median 3Q Max
## -706.90 -134.73 32.45 191.81 526.37
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.239e+02 7.313e+02 -0.306 0.766
## obs_mask -4.426e+02 7.788e+02 -0.568 0.582
## PERCENT_POSITIVE 1.980e+02 2.772e+01 7.143 3.13e-05 ***
## POP_DENOMINATOR -2.770e-04 6.201e-03 -0.045 0.965
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 392 on 10 degrees of freedom
## Multiple R-squared: 0.8978, Adjusted R-squared: 0.8672
## F-statistic: 29.3 on 3 and 10 DF, p-value: 2.88e-05
summary(nomask.data_0713)
##
## Call:
## lm(formula = COVID_CASE_RATE ~ PERCENT_POSITIVE + POP_DENOMINATOR,
## data = data_0713)
##
## Residuals:
## Min 1Q Median 3Q Max
## -691.10 -64.02 32.04 212.52 563.41
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.646e+02 4.059e+02 -1.391 0.192
## PERCENT_POSITIVE 2.069e+02 2.214e+01 9.344 1.45e-06 ***
## POP_DENOMINATOR -2.520e-03 4.633e-03 -0.544 0.597
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 379.7 on 11 degrees of freedom
## Multiple R-squared: 0.8945, Adjusted R-squared: 0.8754
## F-statistic: 46.66 on 2 and 11 DF, p-value: 4.234e-06
anova(mask.data_0713, nomask.data_0713)
## Analysis of Variance Table
##
## Model 1: COVID_CASE_RATE ~ obs_mask + PERCENT_POSITIVE + POP_DENOMINATOR
## Model 2: COVID_CASE_RATE ~ PERCENT_POSITIVE + POP_DENOMINATOR
## Res.Df RSS Df Sum of Sq F Pr(>F)
## 1 10 1536593
## 2 11 1586234 -1 -49642 0.3231 0.5823
confint(mask.data_0713)
## 2.5 % 97.5 %
## (Intercept) -1.853277e+03 1.405406e+03
## obs_mask -2.177823e+03 1.292549e+03
## PERCENT_POSITIVE 1.362476e+02 2.597779e+02
## POP_DENOMINATOR -1.409353e-02 1.353952e-02
confint(nomask.data_0713)
## 2.5 % 97.5 %
## (Intercept) -1.458022e+03 3.288954e+02
## PERCENT_POSITIVE 1.581870e+02 2.556648e+02
## POP_DENOMINATOR -1.271785e-02 7.677142e-03
autoplot(mask.data_0713)
autoplot(nomask.data_0713)
